Abstract: Quantization matrices facilitate digital audio encoding and decoding. An audio encoder generates and compresses quantization matrices; an audio decoder decompresses and applies the quantization matrices. For example, the audio encoder includes a multi-channel transformer operable to output multi-channel audio data in jointly coded channels and a program module for generating a single quantization matrix for weighting all of the jointly coded channels. In one such example, the program module computes the single quantization matrix from an aggregation of pattern information for all of the jointly coded channels, and the aggregation of pattern information is an aggregate excitation pattern.

Abstract: An audio processing tool measures the quality of reconstructed audio data. For example, an audio encoder measures the quality of a block of reconstructed frequency coefficient data in a quantization loop. The invention includes several techniques and tools, which can be used in combination or separately. First, before measuring quality, the tool normalizes the block to account for variation in block sizes. Second, for the quality measurement, the tool processes the reconstructed data by critical bands, which can differ from the quantization bands used to compress the data. Third, the tool accounts for the masking effect of the reconstructed data, not just the masking effect of the original data. Fourth, the tool band weights the quality measurement, which can be used to account for noise substitution or band truncation. Finally, the tool changes quality measurement techniques depending on the channel coding mode.

Abstract: Quantization matrices facilitate digital audio encoding and decoding. An audio encoder generates and compresses quantization matrices; an audio decoder decompresses and applies the quantization matrices. For example, the audio encoder generates a quantization matrix including weighting factors and processes a set of weighting factors according to a parametric model to switch between a direct representation and a parametric representation of the set of weighting factors, where the parametric representation of the set of weighting factors accounts for audibility of distortion according to a model of human auditory perception. In another example, an audio encoder receives a band weight representation of a ciuantization matrix and compresses the band weight representation of the quantization matrix using linear predictive coding, wherein the compressing includes computing pseudo-autocorrelation values for the quantization matrix.

Abstract: An audio processing tool measures the quality of reconstructed audio data. For example, an audio encoder measures the quality of a block of reconstructed frequency coefficient data in a quantization loop. The invention includes several techniques and tools, which can be used in combination or separately. First, before measuring quality, the tool normalizes the block to account for variation in block sizes. Second, for the quality measurement, the tool processes the reconstructed data by critical bands, which can differ from the quantization bands used to compress the data. Third, the tool accounts for the masking effect of the reconstructed data, not just the masking effect of the original data. Fourth, the tool band weights the quality measurement, which can be used to account for noise substitution or band truncation. Finally, the tool changes quality measurement techniques depending on the channel coding mode.

Abstract: An audio processing tool measures the quality of reconstructed audio data. For example, an audio encoder measures the quality of a block of reconstructed frequency coefficient data in a quantization loop. The invention includes several techniques and tools, which can be used in combination or separately. First, before measuring quality, the tool normalizes the block to account for variation in block sizes. Second, for the quality measurement, the tool processes the reconstructed data by critical bands, which can differ from the quantization bands used to compress the data. Third, the tool accounts for the masking effect of the reconstructed data, not just the masking effect of the original data. Fourth, the tool band weights the quality measurement, which can be used to account for noise substitution or band truncation. Finally, the tool changes quality measurement techniques depending on the channel coding mode.

Abstract: A compressed digital audio signal is transmitted from an audio source along a connection wire to an audio receiver. The digital audio signal can encode digital audio data having different sampling frequencies, frames sizes, and other information. The audio receiver that receives the digital audio signal can decode and convert the compressed digital audio signal into multiple synchronized analog signals, which are used to drive multiple speakers. The audio receiver may also synchronize the audio data with associated video data so that the audio playback and video playback are “in sync”, despite delay introduced by the audio signal decoding at the audio receiver.

Abstract: An audio encoder regulates quality and bitrate with a control strategy. The strategy includes several features. First, an encoder regulates quantization using quality, minimum bit count, and maximum bit count parameters. Second, an encoder regulates quantization using a noise measure that indicates reliability of a complexity measure. Third, an encoder normalizes a control parameter value according to block size for a variable-size block. Fourth, an encoder uses a bit-count control loop de-linked from a quality control loop. Fifth, an encoder addresses non-monotonicity of quality measurement as a function of quantization level when selecting a quantization level. Sixth, an encoder uses particular interpolation rules to find a quantization level in a quality or bit-count control loop. Seventh, an encoder filters a control parameter value to smooth quality. Eighth, an encoder corrects model bias by adjusting a control parameter value in view of current buffer fullness.

Abstract: An audio encoder regulates quality and bitrate with a control strategy. The strategy includes several features. First, an encoder regulates quantization using quality, minimum bit count, and maximum bit count parameters. Second, an encoder regulates quantization using a noise measure that indicates reliability of a complexity measure. Third, an encoder normalizes a control parameter value according to block size for a variable-size block. Fourth, an encoder uses a bit-count control loop de-linked from a quality control loop. Fifth, an encoder addresses non-monotonicity of quality measurement as a function of quantization level when selecting a quantization level. Sixth, an encoder uses particular interpolation rules to find a quantization level in a quality or bit-count control loop. Seventh, an encoder filters a control parameter value to smooth quality. Eighth, an encoder corrects model bias by adjusting a control parameter value in view of current buffer fullness.

Abstract: Described techniques and tools include techniques and tools for mapping digital media data (e.g., audio, video, still images, and/or text, among others) in a given format to a transport or file container format useful for encoding the data on optical disks such as digital video disks (DVDs). A digital media universal elementary stream can be used to map digital media streams (e.g., an audio stream, video stream or an image) into any arbitrary transport or file container, including optical disk formats, and other transports, such as broadcast streams, wireless transmissions, etc. The information to decode any given frame of the digital media in the stream can be carried in each coded frame. A digital media universal elementary stream includes stream components called chunks. An implementation of a digital media universal elementary stream arranges data for a media stream in frames, the frames having one or more chunks.

Abstract: Quantization matrices facilitate digital audio encoding and decoding. An audio encoder generates and compresses quantization matrices; an audio decoder decompresses and applies the quantization matrices. The invention includes several techniques and tools, which can be used in combination or separately. For example, the audio encoder can generate quantization matrices from critical band patterns for blocks of audio data. The encoder can compute the quantization matrices directly from the critical band patterns, which can be computed from the same audio data that is being compressed. The audio encoder/decoder can use different modes for generating/applying quantization matrices depending on the coding channel mode of multi-channel audio data. The audio encoder/decoder can use different compression/decompression modes for the quantization matrices, including a parametric compression/decompression mode.

Abstract: An audio encoder regulates quality and bitrate with a control strategy. The strategy includes several features. First, an encoder regulates quantization using quality, minimum bit count, and maximum bit count parameters. Second, an encoder regulates quantization using a noise measure that indicates reliability of a complexity measure. Third, an encoder normalizes a control parameter value according to block size for a variable-size block. Fourth, an encoder uses a bit-count control loop de-linked from a quality control loop. Fifth, an encoder addresses non-monotonicity of quality measurement as a function of quantization level when selecting a quantization level. Sixth, an encoder uses particular interpolation rules to find a quantization level In a quality or bit-count control loop. Seventh, an encoder filters a control parameter value to smooth quality. Eighth, an encoder corrects model bias by adjusting a control parameter value in view of current buffer fullness.

Abstract: An audio encoder regulates quality and bitrate with a control strategy. The strategy includes several features. First, an encoder regulates quantization using quality, minimum bit count, and maximum bit count parameters. Second, an encoder regulates quantization using a noise measure that indicates reliability of a complexity measure. Third, an encoder normalizes a control parameter value according to block size for a variable-size block. Fourth, an encoder uses a bit-count control loop de-linked from a quality control loop. Fifth, an encoder addresses non-monotonicity of quality measurement as a function of quantization level when selecting a quantization level. Sixth, an encoder uses particular interpolation rules to find a quantization level in a quality or bit-count control loop. Seventh, an encoder filters a control parameter value to smooth quality. Eighth, an encoder corrects model bias by adjusting a control parameter value in view of current buffer fullness.

Abstract: Quantization matrices facilitate digital audio encoding and decoding. An audio encoder generates and compresses quantization matrices; an audio decoder decompresses and applies the quantization matrices. The invention includes several techniques and tools, which can be used in combination or separately. For example, the audio encoder can generate quantization matrices from critical band patterns for blocks of audio data. The encoder can compute the quantization matrices directly from the critical band patterns, which can be computed from the same audio data that is being compressed. The audio encoder/decoder can use different modes for generating/applying quantization matrices depending on the coding channel mode of multi-channel audio data. The audio encoder/decoder can use different compression/decompression modes for the quantization matrices, including a parametric compression/decompression mode.

Abstract: Quantization matrices facilitate digital audio encoding and decoding. An audio encoder generates and compresses quantization matrices; an audio decoder decompresses and applies the quantization matrices. The invention includes several techniques and tools, which can be used in combination or separately. For example, the audio encoder can generate quantization matrices from critical band patterns for blocks of audio data. The encoder can compute the quantization matrices directly from the critical band patterns, which can be computed from the same audio data that is being compressed. The audio encoder/decoder can use different modes for generating/applying quantization matrices depending on the coding channel mode of multi-channel audio data. The audio encoder/decoder can use different compression/decompression modes for the quantization matrices, including a parametric compression/decompression mode.

Abstract: Quantization matrices facilitate digital audio encoding and decoding. An audio encoder generates and compresses quantization matrices; an audio decoder decompresses and applies the quantization matrices. The invention includes several techniques and tools, which can be used in combination or separately. For example, the audio encoder can generate quantization matrices from critical band patterns for blocks of audio data. The encoder can compute the quantization matrices directly from the critical band patterns, which can be computed from the same audio data that is being compressed. The audio encoder/decoder can use different modes for generating/applying quantization matrices depending on the coding channel mode of multi-channel audio data. The audio encoder/decoder can use different compression/decompression modes for the quantization matrices, including a parametric compression/decompression mode.

Abstract: An audio encoder regulates quality and bitrate with a control strategy. The strategy includes several features. First, an encoder regulates quantization using quality, minimum bit count, and maximum bit count parameters. Second, an encoder regulates quantization using a noise measure that indicates reliability of a complexity measure. Third, an encoder normalizes a control parameter value according to block size for a variable-size block. Fourth, an encoder uses a bit-count control loop de-linked from a quality control loop. Fifth, an encoder addresses non-monotonicity of quality measurement as a function of quantization level when selecting a quantization level. Sixth, an encoder uses particular interpolation rules to find a quantization level in a quality or bit-count control loop. Seventh, an encoder filters a control parameter value to smooth quality. Eighth, an encoder corrects model bias by adjusting a control parameter value in view of current buffer fullness.

Abstract: An audio encoder regulates quality and bitrate with a control strategy. The strategy includes several features. First, an encoder regulates quantization using quality, minimum bit count, and maximum bit count parameters. Second, an encoder regulates quantization using a noise measure that indicates reliability of a complexity measure. Third, an encoder normalizes a control parameter value according to block size for a variable-size block. Fourth, an encoder uses a bit-count control loop de-linked from a quality control loop. Fifth, an encoder addresses non-monotonicity of quality measurement as a function of quantization level when selecting a quantization level. Sixth, an encoder uses particular interpolation rules to find a quantization level in a quality or bit-count control loop. Seventh, an encoder filters a control parameter value to smooth quality. Eighth, an encoder corrects model bias by adjusting a control parameter value in view of current buffer fullness.

Abstract: An audio encoder regulates quality and bitrate with a control strategy. The strategy includes several features. First, an encoder regulates quantization using quality, minimum bit count, and maximum bit count parameters. Second, an encoder regulates quantization using a noise measure that indicates reliability of a complexity measure. Third, an encoder normalizes a control parameter value according to block size for a variable-size block. Fourth, an encoder uses a bit-count control loop de-linked from a quality control loop. Fifth, an encoder addresses non-monotonicity of quality measurement as a function of quantization level when selecting a quantization level. Sixth, an encoder uses particular interpolation rules to find a quantization level in a quality or bit-count control loop. Seventh, an encoder filters a control parameter value to smooth quality. Eighth, an encoder corrects model bias by adjusting a control parameter value in view of current buffer fullness.

Abstract: An audio encoder regulates quality and bitrate with a control strategy. The strategy includes several features. First, an encoder regulates quantization using quality, minimum bit count, and maximum bit count parameters. Second, an encoder regulates quantization using a noise measure that indicates reliability of a complexity measure. Third, an encoder normalizes a control parameter value according to block size for a variable-size block. Fourth, an encoder uses a bit-count control loop de-linked from a quality control loop. Fifth, an encoder addresses non-monotonicity of quality measurement as a function of quantization level when selecting a quantization level. Sixth, an encoder uses particular interpolation rules to find a quantization level in a quality or bit-count control loop. Seventh, an encoder filters a control parameter value to smooth quality. Eighth, an encoder corrects model bias by adjusting a control parameter value in view of current buffer fullness.

Abstract: An encoder uses multi-pass VBR control strategies to provide constant or relatively constant quality for VBR output while guaranteeing (within tolerance) either compressed file size or, equivalently, overall average bitrate. The control strategies include various techniques and tools, which can be used in combination or independently. For example, in a first pass, an audio encoder encodes a sequence of audio data partitioned into variable-size chunks. In a second pass, the encoder encodes the sequence according to control parameters to produce output of relatively constant quality. The encoder sets checkpoints in the second pass to adjust the control parameters and/or subsequent checkpoints. The encoder selectively considers a peak bitrate constraint to limit peak bitrate. The encoder stores auxiliary information from the first pass for use in the second pass, which increases the speed of the second pass. Finally, the encoder compares signatures for the input data to check consistency between passes.